Construction of fuzzy ¯ X - S control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable

Monitoring road accident and injury using indeterminacy based Shewhart control chart using multiple dependent state repetitive sampling

The uncertainty/indeterminate in control chart parameter/observations affects the performance of the control chart. This paper addresses the indeterminacy and its effect on the Shewhart X-bar control using multiple dependent state repetitive sampling. The probabilities and neutrosophic average run length for in-control and out-of-control processes are derived. The tables and figures of the proposed chart are presented when uncertainty/indeterminate is present in sample size and proceeding subgroups. The efficiency of the proposed chart is compared with the existing charts and the proposed chart is found to be efficient in terms of neutrosophic average run length.

Design of SN2-NEWMA Control Chart for Monitoring Process having Indeterminate Production Data

The existing charts for monitoring the variance are designed under the assumption that all production data must consist of exact, precise, and determined observations. This paper presents the design of a new neutrosophic exponentially weighted moving average (NEWMA) combining with a neutrosophic logarithmic transformation chart for monitoring the variance having neutrosophic numbers. The computation of the neutrosophic control chart parameters is done through the neutrosophic Monte Carlo simulation (NMCS). The performance of the proposed chart is discussed with the existing charts.

Control Chart for Failure-Censored Reliability Tests under Uncertainty Environment

Existing control charts based on failure-censored (Type-II) reliability tests were designed using classical statistics. Classical statistics was applied for the monitoring of the process when observations in the sample or the population were determined. Neutrosophic statistics (NS) are applied when there is uncertainty in the sample or population. In this paper, a control chart for failure-censored (Type-II) reliability tests was designed using NS. The design of a control chart for the Weibull distribution, which is applied when there is a lack of symmetry using neutrosophic statistics, is given. The proposed control chart was used to monitor the neutrosophic mean and neutrosophic variance, which are related to the neutrosophic scale parameter. The advantages of the proposed control chart over the existing control chart are discussed.

Monitoring the Variability in the Process Using Neutrosophic Statistical Interval Method

Existing variance control charts are designed under the assumptions that no uncertain, fuzzy and imprecise observations or parameters are in the population or the sample. Neutrosophic statistics, which is the extension of classical statistics, has been widely used when there is uncertainty in the data. In this paper, we will originally design S 2 control chart under the neutrosophic interval methods. The complete structure of the neutrosophic S 2 control chart will be given. The necessary measures of neutrosophic S 2 will be given. The neutrosophic coefficient of S 2 control chart will be determined through the neutrosophic algorithm. Some tables are given for practical use. The efficiency of the proposed control chart is shown over the S 2 control chart designed under the classical statistics in neutrosophic average run length (NARL). A real example is also added to illustrate the proposed control chart. From the comparison in the simulation study and case study, it is concluded that the proposed control chart performs better than the existing control chart under uncertainty.